Comparison of two measurement devices for obtaining horizontal force-velocity profile variables during sprint running

This study established the magnitude of systematic bias and random error of horizontal force-velocity (F-v) profile variables obtained from a 1080 Sprint compared to that obtained from a Stalker ATS II radar device. Twenty high-school athletes from an American football training group completed a 30 m sprint while the two devices simultaneously measured velocity-time data. The velocity-time data were modelled by an exponential equation fitting process and then used to calculate individual F-v profiles and related variables (theoretical maximum velocity, theoretical maximum horizontal force, slope of the linear F-v profile, peak power, time constant tau, and horizontal maximal velocity). The devices were compared by determining the systematic bias and the 95% limits of agreement (random error) for all variables, both of which were expressed as percentages of the mean radar value. All bias values were within 6.32%, with the 1080 Sprint reporting higher values for tau, horizontal maximal velocity, and theoretical maximum velocity. Random error was lowest for velocity-based variables but exceeded 7% for all others, with slope of the F-v profile being greatest at ±12.3%. These results provide practitioners with the information necessary to determine if the agreement between the devices and the magnitude of random error is acceptable within the context of their specific application.

Rheology of crossbridge ensembles

Muscle rheology, or the characterization of a muscle's response to external mechanical perturbations, is crucial to an animal's motor control and locomotive abilities. How the rheology emerges from the ensemble dynamics of microscopic actomyosin crossbridges known to underlie muscle forces is however a longstanding question. Classical descriptions in terms of force-length and force-velocity relationships capture only part of the rheology, namely under steady but not dynamical conditions. Although much is known about the actomyosin machinery, current mathematical models that describe the behavior of a population or an ensemble of crossbridges are plagued by an excess of parameters and computational complexity that limits their usage in large-scale musculoskeletal simulations. In this paper, we examine models of crossbridge dynamics of varying complexity and show that the emergent rheology of an ensemble of crossbridges can be simplified to a few dominant time-constants associated with intrinsic dynamical processes. For Huxley's classical two-state crossbridge model, we derive exact analytical expressions for the emergent ensemble rheology and find that it is characterized by a single time-constant. For more complex models with up to five crossbridge states, we show that at most three time-constants are needed to capture the ensemble rheology. Our results thus yield simplified models comprising of a few time-constants for muscle's bulk rheological response that can be readily used in large-scale simulations without sacrificing the model's interpretability in terms of the underlying actomyosin crossbridge dynamics.

Relationships between Strength and Step Frequency with Fatigue Index in Repeated Sprint Ability

Force−velocity profile (FVP) and repeated-sprint ability (RSA) tests are indicators of physical capacities in most team sport players. The purpose of this study was to examine the stride kinematics during a repeated-sprint ability (RSA) test and to analyze the relationship between Bosco’s force−velocity profile (FVP) and RSA performance in elite female field hockey players. Thirteen elite-female players performed both RSA (six 30 m maximal sprints) and jumping (CMJ weighted and body weight) tests. Sprinting time fatigue indexes during a 30 m RSA test were correlated with step frequency fatigue indexes (r > 0.7; p < 0.01). CMJ50 showed a large relationship with sprint time fatigue indexes. FV50 showed a very large relationship with sprint time fatigue indexes (r > 0.7; p < 0.01), and a large relationship with the step frequency fatigue indexes (r > 0.5; p < 0.05). This study highlighted two possible ways to improve fatigue indexes in RSA, with the aim of maximizing the distances covered at high-intensities during the matches: (a) strength training and (b) focusing on step frequency during speed training.

Modeling Optimal Cadence as a Function of Time during Maximal Sprint Exercises Can Improve Performance by Elite Track Cyclists

In track cycling sprint events, optimal cadence PRopt is a dynamic aspect of fatigue. It is currently unclear what cadence is optimal for an athlete’s performance in sprint races and how it can be calculated. We examined fatigue-induced changes in optimal cadence during a maximal sprint using a mathematical approach. Nine elite track cyclists completed a 6-s high-frequency pedaling test and a 60-s isokinetic all-out sprint on a bicycle ergometer with continuous monitoring of crank force and cadence. Fatigue-free force-velocity (F/v) and power-velocity (P/v) profiles were derived from both tests. The development of fatigue during the 60-s sprint was assessed by fixing the slope of the fatigue-free F/v profile. Fatigue-induced alterations in PRopt were determined by non-linear regression analysis using a mono-exponential equation at constant slope. The study revealed that PRopt at any instant during a 60-s maximal sprint can be estimated accurately using a mono-exponential equation. In an isokinetic mode, a mean PRopt can be identified that enables the athlete to generate the highest mean power output over the course of the effort. Adding the time domain to the fatigue-free F/v and P/v profiles allows time-dependent cycling power to be modelled independent of cadence.

No Effect of Cycling Shoe Outsole Stiffness On Sub- and Supra-Maximal Cycling Performance Parameters.

Background: The aim of this study was to test the effects of cycling shoe outsole stiffness on both performance and comfort parameters during sub- and supra-maximal cycling tests. Methods: Two groups of recreational women tested three cycling shoe conditions with differing outsole stiffness. One group of 8 women performed four cycling tests of 3 min composed of two intensities (100 and 140 W) and two pedaling rates (70 and 100 rpm) for each pair of shoes. Metabolic and subjective perception of comfort measurement was evaluated with each shoe. Another group of 12 women performed 6-s all-out sprints against two external resistances (0.4 and 0.7 N/kg) to determine force-velocity relationships with the three cycling shoe conditions. Results: The main findings are that the stiffness of the investigated outsole cycling shoes (i) does not influence cycling performance whatever the test (ii) while the perception of comfort is largely degraded compared to the most flexible shoe. Conclusion: Maximizing stiffness should no longer be of the highest design principal for beginners or recreational women cyclists.

Development and Validation of Prediction Formula of Wingate Test Peak Power From Force–Velocity Test in Male Soccer Players

Peak power of the Wingate anaerobic test (WAnT), either in W (Ppeak) or in W.kg–1 (rPpeak), has been widely used to evaluate the performance of soccer players; however, its relationship with force–velocity (F-v) test (e.g., whether these tests can be used interchangeably) has received little scientific attention so far. The aim of this work was to develop and validate a prediction equation of Ppeak and rPpeak from F-v characteristics in male soccer players. Participants were 158 adult male soccer players (sport experience 11.4 ± 4.5 years, mean ± standard deviation, approximately five weekly training units, age 22.6 ± 3.9 years, body mass 74.8 ± 7.8 kg, and height 178.3 ± 7.8 cm) who performed both WAnT and F-v test. An experimental (EXP, n = 79) and a control group (CON, n = 79) were used for development and validation, respectively, of the prediction equation of Ppeak and rPpeak from F-v test. In EXP, Ppeak correlated very largely with body mass (r = 0.787), fat-free mass (r = 0.765), largely with maximal power of F-v test (Pmax; r = 0.639), body mass index (r = 0.603), height (r = 0.558), moderately with theoretical maximal force (F0; r = 0.481), percentage of body fat (r = 0.471), fat mass (r = 0.443, p &lt; 0.001); rPpeak correlated with rPmax (largely; r = 0.596, p &lt; 0.001), theoretical maximal velocity (v0; moderately; r = 0.341, p = 0.002), F0 (small magnitude; r = 0.280, p = 0.012), BF (r = −0.230, p = 0.042), and fat mass (r = −0.242, p = 0.032). Ppeak in EXP could be predicted using the formula “44.251 + 7.431 × body mass (kg) + 0.576 × Pmax (W) – 19.512 × F0” (R = 0.912, R2 = 0.833, standard error of estimate (SEE) = 42.616), and rPpeak from “3.148 + 0.218 × rPmax (W.kg–1) + v0 (rpm)” (R = 0.765, R2 = 0.585, SEE = 0.514). Applying these formulas in CON, no bias was observed between the actual and the predicted Ppeak (mean difference 2.5 ± 49.8 W; 95% CI, −8.7, 13.6; p = 0.661) and rPpeak (mean difference 0.05 ± 0.71 W.kg–1; 95% CI, −0.11, 0.21, p = 0.525). These findings provided indirect estimates of Ppeak of the WAnT, especially useful in periods when this test should not be applied considering the fatigue it causes; in this context, the F-v test can be considered as an alternative of exercise testing for estimating the average Ppeak of a group of soccer players rather than for predicting individual scores when the interindividual variation of performance is small.

The Association Between Force-Velocity Relationship in Countermovement Jump and Sprint With Approach Jump, Linear Acceleration and Change of Direction Ability in Volleyball Players

The force-velocity (FV) relationship allows the identification of the mechanical capabilities of musculoskeletal system to produce force, power and velocity. The aim of this study was to assess the associations of the mechanical variables derived from the FV relationship with approach jump, linear sprint and change of direction (CoD) ability in young male volleyball players. Thirty-seven participants performed countermovement jumps with incremental loads from bodyweight to 50–100 kg (depending on the individual capabilities), 25-m sprint with split times being recorded for the purpose of FV relationship calculation, two CoD tests (505 test and modified T-test) and approach jump. Results in this study show that approach jump performance seems to be influenced by maximal power output (r = 0.53) and horizontal force production (r = 0.51) in sprinting, as well as force capacity in jumping (r = 0.45). Only the FV variables obtained from sprinting alone contributed to explaining linear sprinting and CoD ability (r = 0.35–0.93). An interesting finding is that sprinting FV variables have similar and some even stronger correlation with approach jump performance than jumping FV variables, which needs to be considered for volleyball training optimization. Based on the results of this study it seems that parameters that refer to horizontal movement capacity are important for volleyball athletic performance. Further interventional studies are needed to check how to implement specific FV-profile-based training programs to improve specific mechanical capabilities that determine volleyball athletic performance and influence the specific physical performance of volleyball players.

Assessment and Evaluation of Force–Velocity Variables in Flywheel Squats: Validity and Reliability of Force Plates, a Linear Encoder Sensor, and a Rotary Encoder Sensor

Research into flywheel (FW) resistance training and force–velocity–power (F–v–P) profiling has recently gained attention. Ground reaction force (GRF) and velocity (v) during FW squats can be predicted from shaft rotational data. Our study aimed to compare the inter-set reliability of GRF, v, and F–v–P relationship output variables calculated from force plates and linear encoder (presumed gold-standard) and rotary encoder data. Fifty participants performed two sets of FW squats at four inertias. Peak and mean concentric and eccentric GRF, v, and F–v–P outcomes from mean variables during the concentric phase of the squat were calculated. Good to excellent reliability was found for GRF and v (ICC > 0.85), regardless of the measure and the variable type. The F–v–P outcomes showed moderate to good reliability (ICC > 0.74). Inter-measure bias (p < 0.05) was found in the majority of GRF and v variables, as well as for all the calculated F–v–P outcomes (trivial to large TEs) with very large to perfect correlations for v (r 0.797–0.948), GRF (r 0.712–0.959), and, finally, F–v–P outcomes (ICC 0.737–0.943). Rotary encoder overestimated the force plates and linear encoder variables, and the differences were dependent on the level of inertia. Despite high reliability, FW device users should be aware of the discrepancy between the measures.